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Improvements in Statistical Tropical Cyclone Forecast Models: A Year 2 Joint Hurricane Testbed Project Update Mark DeMaria 1, Andrea Schumacher 2, John.

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Presentation on theme: "Improvements in Statistical Tropical Cyclone Forecast Models: A Year 2 Joint Hurricane Testbed Project Update Mark DeMaria 1, Andrea Schumacher 2, John."— Presentation transcript:

1 Improvements in Statistical Tropical Cyclone Forecast Models: A Year 2 Joint Hurricane Testbed Project Update Mark DeMaria 1, Andrea Schumacher 2, John A. Knaff 1 and Renate Brummer 2 1 NOAA/NESDIS, Fort Collins, CO 2 CIRA, Colorado State University, Fort Collins, CO NHC POCs: Lixion Avila, Robbie Berg, Chris Landsea Interdepartmental Hurricane Conference March 2013

2 Outline Project Tasks 1.Extended range baseline models for track and intensity 2.Update of SHIPS/LGEM databases using new NCEP Climate Re-analysis 3.Extending LGEM to 7 days 4.SHIPS/LGEM specific for the Gulf of Mexico Progress so far Plans for 2013 season 2

3 1. New Baseline Forecast Models CLIPER and SHIFOR used as baseline for measuring track and intensity forecast skill –Errors provide estimate of forecast difficulty Input to linear regression equations –t = 0 h max wind, lat, lon, motion vector –t =-12h max wind, lat, lon, motion vector –Julian Day Output –5-day forecast of lat, lon, max wind Decay-SHIFOR modifies intensity over land using CLIPER track and climatological decay rate 3

4 Trajectory Approach for Baseline Models (T-CLIPER) dx/dt = u dy/dt = v (1) Estimate u,v from climatological motion vector fields Modify u,v at early times using t=0 motion vector Integrate (1) to desired time Similar approach for intensity using LGEM prediction equation with climatological input and T-CLIPER track Can be run to any forecast time until storm leaves model domain 4

5 Mean Storm Motion Fields from Sample 5

6 T-CLIPER Tests Run in real time for most of 2012 season Re-runs for using CARQ input Evaluation questions –How do average errors compare with OCD5 to 5 days? –Are annual average T-CLIPER errors correlated with NHC OFCL forecast errors? –What is the error behavior beyond 5 days? 6

7 Comparison of T-CLIPER and OCD5 10-year Average Errors 7

8 Correlation of Annual OCD5 and T-CLIPER Errors with OFCL Correlate OCD5 and OFCL annual errors for 10 year sample Repeat for T- CLIPER and OFCL Plot r 2 versus forecast interval –Plot r 2 as negative if r is negative 8

9 Variance of OFCL Errors Explained by OCD5 and T-CLIPER 9

10 10-Year Average T-CLIPER Errors Track Intensity 10

11 2. New Climate Reanalysis Fields New NCEP CFSR reanalysis fields obtained for –0.5 o lat/lon grib files Current SHIPS database – Old NCEP reanalysis (2.5 o ) – Operational GFS analyses (2 o ) Inconsistency of RH and GFS vortex parameters Old reanalysis not used in RII –Incomplete operational analyses used for – New, Old reanalysis and Operational analyses all available 11

12 Comparison of SHIPS Predictors for Different Analyses ( Atlantic Sample) 12 RHLO = hPa RH r=200 to 800 km RHMD = hPa RH r=200 to 800 km GFS Vortex = 850 hPa tangential wind, r= 0 to 600 km

13 New SHIPS Database : New NCEP reanalysis (1 o ) : Operational GFS analysis (1 o ) 2013 SHIPS, LGEM and RII will all use the same database 13

14 3. Seven-Day LGEM Small sample size beyond 5 days makes fitting difficult Use new formulation of LGEM that fits entire forecast at once Sample

15 Comparison of Fitting Methods LGEM Equation: dV/dt = V – β(V/V mpi ) n V β, n, V mpi known or specified, need to find Old fitting method –Solve for : = (1/V)dV/dt + β(V/V mpi ) n V –Calculate from best track –Fit best track to predictors using least squares at each forecast period (6, 12 …, 168 h) New fitting method –Define cost function E = ½ (V fcst -V obs )dt –Find single set of coefficients to minimize E Requires adjoint of LGEM equation for fitting 15

16 Features of 7-Day LGEM Adjoint minimization instead of least squares fit to –Need to reduce predictor set for efficiency Replace simple empirical MPI function with theoretical Bister and Emanuel (2003) formula –Can incorporate SST cooling and entrainment in MPI formula Include persistence and GOES data through modification of at early times –Similar to T-CLIPER approach 16

17 4. Gulf of Mexico LGEM Rappaport et al. (2010) showed Gulf storms have consistent behavior –Gulf-specific SHIPS/LGEM may improve skill Gulf sample size very small, especially beyond 72 h –Use same formulation as 7-Day LGEM –Add new Gulf cases from

18 Plans for 2013 Hurricane Season Run standard 5-day SHIPS/LGEM Run parallel 7-day LGEM with new formulation –Includes Gulf-specific version Pre-season tests –Run on HFIP stream 1.5 retrospective cases sample –Only 2012 to 7 days since NHC track needed –Run for cases with recon 18

19 Summary T-CLIPER provides new extended range forecast baseline –Errors within +8% to -5% of OCD5 to 5 days –Predicts OFCL intensity error similar to OCD5 –Predicts OFCL track errors better than OCD5 New NCEP reanalysis provides more consistent and higher resolution developmental sample 7-day and Gulf-specific LGEM to be run in parallel in 2013 season SHIPS/LGEM/RII being developed for W. Pacific, Indian Ocean and S. Hemisphere Acknowledgement: This NOAA Joint Hurricane Testbed project was funded by the US Weather Research Program in NOAA/OAR's Office of Weather and Air Quality 19


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